{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T18:15:44Z","timestamp":1781633744367,"version":"3.54.5"},"posted":{"date-parts":[[2026,2,8]]},"group-title":"Biophysics","reference-count":40,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T00:00:00Z","timestamp":1770508800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"crossref","award":["R35GM142719"],"award-info":[{"award-number":["R35GM142719"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"crossref"}]},{"name":"NSF ACCESS","award":["CHE180027P"],"award-info":[{"award-number":["CHE180027P"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,2,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Virtual screening for small-molecule binders is often limited by false positives from approximate scoring functions and rigid-receptor assumptions. These can be addressed downstream through accurate but expensive free energy calculations. At the same time, recent artificial-intelligence-based co-folding methods have been proposed that claim to achieve accuracy of free energy methods at much lower cost, but these have not yet delivered consistent improvements in early enrichment and can be confounded by memorization. Here we address this gap by introducing c(t)-based metadynamics (CTMD), a physics-based, high-throughput hit-triaging protocol tailored for early enrichment. CTMD uses the nonequilibrium reversible-work estimator\n                  <jats:italic>c<\/jats:italic>\n                  (\n                  <jats:italic>t<\/jats:italic>\n                  ) introduced by Tiwary and Parrinello (Journal of Physical Chemistry B, 2015 119 736), computed from a small number of short, independent well-tempered metadynamics trajectories, to rank binding stability without requiring converged binding free energies. Across diverse targets and chemotypes, CTMD provides robust early enrichment while remaining fast, transferable with minimal parameter tuning, and resistant to memorization-driven artifacts\u2014underscoring both an immediately deployable physics-based alternative for screening. For these systems we show how co-folding, particularly Boltz-2, achieves enrichment directly proportional to similairty with training set, and more worrying, even in the presence of signficant modifications to active site. Given its simplicity of implementation, CTMD should thus be an \u201cembarassingly\u201d open-source, early enrichment method available for use by the broad pharma and academic community that sits right between approximate but fast docking or AI based co-folding methods, and more expensive but accurate free energy calculations, expected to lead to saving significant financial and human capital in drug discovery campaigns.\n                <\/jats:p>","DOI":"10.64898\/2026.02.05.703972","type":"posted-content","created":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T01:20:12Z","timestamp":1770600012000},"source":"Crossref","is-referenced-by-count":1,"title":["Early-Enrichment Hit Discovery via Reversible-Work c(t) Estimation in Metadynamics (CTMD)"],"prefix":"10.64898","author":[{"given":"Venkata Sai Sreyas","family":"Adury","sequence":"first","affiliation":[{"name":"Biophysics Program and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pratyush","family":"Tiwary","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Biochemistry and Institute for Physical Science and Technology, University of Maryland, College Park 20742, USA"},{"name":"Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Gu","sequence":"additional","affiliation":[{"name":"Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mrinal","family":"Shekhar","sequence":"additional","affiliation":[{"name":"University of Maryland Institute for Health Computing, Bethesda 20852, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026021103501419000_2026.02.05.703972v1.1","first-page":"853","volume":"13","year":"2021","journal-title":"Am J Transl Res"},{"key":"2026021103501419000_2026.02.05.703972v1.2","doi-asserted-by":"crossref","first-page":"13121","DOI":"10.3390\/ijms252313121","volume":"25","year":"2024","journal-title":"Int. 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